distributions3
distributions3 0.3.0 adds sample-based distributions and likelihood derivatives
A side-by-side editorial comparison of esquisse and tulpa — release velocity, themes, recent moves, and the top alternatives to consider.
esquisse's 1.0 turned a point-and-click addin into embeddable Shiny modules.
The visible history covers the 1.0 line only. 1.0.0 is the substantial one: modules for importing data (via datamods) and exporting plots, a `ggplot_output()` / `render_ggplot()` pair, manual colour palettes, aesthetic parameter selection, more export formats including pptx, and typography controls. 1.0.1 and 1.0.2 are corrective — sf object handling, package-sourced data, disabled-panel label controls, and an `output_format` argument on the save modal.
The 0.0.x train stops at CRAN: tulpa's engine ships to the ecosystem it already anchors.
tulpa is the C++/R Bayesian spatial inference engine sitting under gcol33's family of ecological occupancy packages, tagging 0.0.x releases several times a week. 0.1.0 is its first CRAN release, and the notes state outright that the engine surface is unchanged from 0.0.198 — the work is packaging discipline: local T bindings rebound to n_t/n_times, OpenMP teams capped under R CMD check, the pkgdown deploy narrowed, an aspell dictionary added. The window behind it splits between the S3 generics conversion and numerical-correctness work in the nested-Laplace grid.
The visible history covers the 1.0 line only. 1.0.0 is the substantial one: modules for importing data (via datamods) and exporting plots, a `ggplot_output()` / `render_ggplot()` pair, manual colour palettes, aesthetic parameter selection, more export formats including pptx, and typography controls. 1.0.1 and 1.0.2 are corrective — sf object handling, package-sourced data, disabled-panel label controls, and an `output_format` argument on the save modal.
The arc runs from a self-contained RStudio addin toward a component library other people build with: once plot rendering and export exist as Shiny modules, esquisse's ggplot builder can be dropped inside someone else's app rather than only launched beside RStudio. The two follow-up releases are consolidation on that surface rather than expansion of it.
Further work most likely lands on the module API and export coverage, since that is where 1.0.0 put the new surface and where 1.0.2 already returned. The entries do not indicate anything about cadence beyond this line.
tulpa is the C++/R Bayesian spatial inference engine sitting under gcol33's family of ecological occupancy packages, tagging 0.0.x releases several times a week. 0.1.0 is its first CRAN release, and the notes state outright that the engine surface is unchanged from 0.0.198 — the work is packaging discipline: local T bindings rebound to n_t/n_times, OpenMP teams capped under R CMD check, the pkgdown deploy narrowed, an aspell dictionary added. The window behind it splits between the S3 generics conversion and numerical-correctness work in the nested-Laplace grid.
Two moves in nine days point at the same destination: the generics conversion made tulpa extensible by downstream packages, and CRAN admission makes it installable by them. The current cadence — several tags a week, some existing only to record a measurement that produced no code change — does not survive CRAN's submission overhead, so the release rhythm has to slow whether or not the project intends it. The correctness work still clusters on the joint nested-Laplace driver, and 0.1.0 extends the same diagnostics habit with .NL_AXIS_SD_REASONS, a closed vocabulary for an outer axis whose grid does not contain its own posterior mode.
Expect tulpaObs to follow tulpa onto CRAN, since it is the consumer whose registrations the engine has spent this window unblocking, and expect the version line to move in larger, less frequent steps now that each one carries a submission.
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either esquisse or tulpa.
distributions3 0.3.0 adds sample-based distributions and likelihood derivatives
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RStudio ships through release branches, and the notes are commit messages
dbt Fusion's second beta is adapter work: ClickHouse gets materializations, indexes, and catalogs
Fulcrum is betting its whole map stack on Esri, with a hard Google Maps cutoff on September 1.
Holistics keeps fencing in the AI layer it spent the summer building.
See all esquisse alternatives → · See all tulpa alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. tulpa is currently shipping more aggressively (velocity 7.5 vs 0.0), with 2 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. tulpa is currently shipping more aggressively (velocity 7.5 vs 0.0), with 2 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top esquisse alternatives in Analytics are ranked by recent ship velocity. Browse the "esquisse alternatives" section above for the current picks, or visit /alternatives/esquisse for the full list with editorial commentary on each.
Top tulpa alternatives in Analytics are ranked by recent ship velocity. Browse the "tulpa alternatives" section above for the current picks, or visit /alternatives/tulpa for the full list with editorial commentary on each.